CN102546088A - BD (block diagonalization) pre-coding method and device - Google Patents

BD (block diagonalization) pre-coding method and device Download PDF

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CN102546088A
CN102546088A CN2010106221758A CN201010622175A CN102546088A CN 102546088 A CN102546088 A CN 102546088A CN 2010106221758 A CN2010106221758 A CN 2010106221758A CN 201010622175 A CN201010622175 A CN 201010622175A CN 102546088 A CN102546088 A CN 102546088A
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matrix
user
lower triangular
channel matrix
precoding
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CN102546088B (en
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杨阳
方舒
罗旬
李少谦
严春林
原田笃
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University of Electronic Science and Technology of China
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University of Electronic Science and Technology of China
NTT Docomo Inc
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Abstract

The invention discloses a BD (block diagonalization) pre-coding method and device, wherein the method comprises the following steps: determining a total user channel matrix Hs according to a downlink channel matrix of each user in a system; carrying out QR factorization on a conjugate transpose matrix of the total user channel matrix Hs to obtain a product of an orthogonal matrix Q and an upper triangular matrix R, and expressing the total user channel matrix Hs as the product of a lower triangular matrix L and a conjugate transpose matrix QH of the orthogonal matrix Q; carrying out inverse calculation on the lower triangular matrix L to obtain L-1; according to the inversed L-1 of the lower triangular matrix L and the orthogonal matrix Q, obtaining a null space orthogonal basis of an interference channel matrix of each user; according to the null space orthogonal basis of the interference channel matrix of each user, constructing a linear pre-coding matrix of each user; and carrying out linear pre-coding on a transmitting signal of each user by utilizing the constructed linear pre-coding matrix. The technical scheme disclosed by the invention can reduce the system complexity and improve the coding efficiency.

Description

Block diagonalization precoding method and device
Technical Field
The present invention relates to the field of wireless communication systems, and in particular, to a Block Diagonalization (BD) precoding method and apparatus.
Background
To achieve higher data rates, conventional multi-user multiple-input single-output (MU-MIMO) systems have been extended to multi-user multiple-input multiple-output (MU-MIMO) systems. However, since multiple users in the MU-MIMO system share the same time and frequency resources, multi-user co-channel interference (CCI) is inevitably introduced, which affects reliable data reception.
To eliminate CCI, the base station needs to first obtain Channel State Information (CSI) reflecting the channel characteristics, for example, to acquire a channel transmission matrix through channel estimation. And then according to the channel state information, selecting a proper linear precoding matrix to carry out linear precoding for eliminating CCI on the transmitting signals, and then sending the transmitting signals to a receiving end.
The BD precoding algorithm is a precoding algorithm widely used in the MU-MIMO system at present, and the main idea of the algorithm comprises the following steps: (1) base station obtains downlink channel matrix H of each userkWhere K is the user index, K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band simultaneously. In a Time Division Duplex (TDD) mode, a base station can acquire a channel matrix estimated by a user through channel reciprocity; in Frequency Division Duplex (FDD) mode, the base station can know the channel matrix from the base station to the user through the feedback of the terminal. (2) Determining an interference channel matrix of any user k according to the obtained downlink channel matrixAnd calculating an interference channel matrix of an arbitrary user k
Figure BSA00000410899400012
By zero-space orthogonal basis, i.e. finding the channel matrix with interference
Figure BSA00000410899400013
The column vectors in (1) are orthogonal vectors. (3) And constructing a precoding matrix of each user according to the calculated zero-space orthogonal basis of the interference channel matrix of each user.
Then, the constructed linear precoding matrix can be used to perform linear precoding processing on the transmission signals of each user. The specific way of performing linear precoding processing may be: and multiplying the linear precoding matrix corresponding to any user by the transmitting signal of the user, and then transmitting the result through a transmitting antenna.
Two conventional BD precoding methods are described below, taking a specific system environment as an example.
Suppose that in a multi-user MIMO system, a base station of a cell has NtA plurality of transmitting antennas, wherein the number of receiving antennas of any user K (K is 1, 2, …, K) is nkAnd K is the number of users served simultaneously by the base station using the same frequency band. The total number of receiving antennas on K user terminals is
Figure BSA00000410899400021
And, the total number of transmitting antennas N of the base stationTGreater than or equal to the total number of receiving antennas N of the user terminalR。
The method comprises the following steps: conventional BD pre-coding methods. The method comprises the following steps:
step 1, the base station obtains the downlink channel matrix H of each userk，k(k＝1，2，…，K)。
Step 2, determining an interference channel matrix of any user k according to the acquired downlink channel matrix
Figure BSA00000410899400022
Dimension of (N)R-nk)×NT(ii) a Wherein [ ·]TRepresenting the transpose of the matrix.
Step 3, interference channel matrix to any user k
Figure BSA00000410899400023
Performing SVD decompositionTo obtain
Figure BSA00000410899400025
Zero space orthogonal basis ofWherein,
Figure BSA00000410899400027
is thatThe left singular matrix of (a) is,
Figure BSA00000410899400029
and
Figure BSA000004108994000210
are respectively
Figure BSA000004108994000211
Front of the right singular matrix
Figure BSA000004108994000212
Column sum
Figure BSA000004108994000213
The columns of the image data are,
Figure BSA000004108994000214
has the dimension of
Figure BSA000004108994000215
[·]HRepresents a conjugate transpose of a matrix, in which
Figure BSA000004108994000216
rank () represents the rank operation of the matrix.
From the above-mentioned zero-space orthogonal basis
Figure BSA000004108994000217
In (1), an arbitrary n is selectedkWith individual column vectors as linear precoding matrices for user kA column vector. Alternatively, the precoding matrix may be constructed as follows in step 4 to step 5.
Step 4, utilizing
Figure BSA000004108994000218
Zero space orthogonal basis of
Figure BSA000004108994000219
And the downlink channel matrix H of user kkConstructing an equivalent channel matrix for user k with completely eliminated CCI (i.e., zero CCI):
Figure BSA000004108994000220
step 5, in order to obtain the maximum pre-coding gain of the equivalent channel matrix with zero CCI, the equivalent channel matrix is again subjected to SVD
Figure BSA000004108994000221
And constructing a precoding matrix of each user according to the decomposition result as follows:
Figure BSA000004108994000222
wherein
Figure BSA000004108994000223
Is a VkFront n ofkAnd (4) columns. Accordingly, the precoding matrix of the whole system is: ws＝[W1 W2…WK]。
In the method, the interference channel matrix of any user k is obtained
Figure BSA000004108994000224
When the zero space orthogonal basis is obtained, the matrix is transmitted through the interference channel
Figure BSA000004108994000225
The SVD decomposition is performed (as shown in step 3), but the computation complexity of the SVD decomposition itself is large, thus resulting in linear pre-coding of the signal at the transmitting endThe code complexity is increased and the linear precoding efficiency is low.
The method 2 comprises the following steps: and (3) a BD pre-coding algorithm based on QR decomposition. Compared with the method 1, the method is different in that: interference channel matrix of any user k is obtained
Figure BSA00000410899400031
Using QR decomposition instead of SVD decomposition, i.e. the method in step 3, the interference channel matrix for any user kPerforming QR decomposition
Figure BSA00000410899400033
To obtain
Figure BSA00000410899400034
Zero space orthogonal basis of
Figure BSA00000410899400035
Then, according to the calculated zero-space orthogonal basis of the interference channel matrix of each user, the process of constructing the precoding matrix of each user can be the same as that of the method 1.
In the method 2, although QR decomposition is used for replacing SVD decomposition, the algorithm complexity is reduced; but because it needs to perform QR decomposition once for the interference channel matrix of each user, the complexity is still high, so that the linear precoding efficiency is still low.
Therefore, the BD precoding method in the prior art has high computational complexity, so that the linear precoding efficiency is low when the CCI is eliminated by using the BD precoding algorithm.
Disclosure of Invention
In view of the above, the present invention provides a BD precoding method on the one hand and a BD precoding device on the other hand, so as to improve the efficiency of linear precoding.
The BD pre-coding method provided by the invention comprises the following steps:
determining a total user channel matrix according to a downlink channel matrix of each user in the system
Figure BSA00000410899400036
Wherein HkA downlink channel matrix of a user K, where K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band;
for the total user channel matrix HsConjugate transpose matrix of
Figure BSA00000410899400037
QR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, and the total user channel matrix H is obtainedsConjugate transpose matrix Q represented as lower triangular matrix L and orthogonal matrix QHWhere L is the conjugate transpose of the upper triangular matrix RH；
Performing inversion calculation on the lower triangular matrix L to obtain
Figure BSA00000410899400038
According to the inverse of the lower triangular matrix L
Figure BSA00000410899400041
Obtaining a zero space orthogonal base of each user interference channel matrix;
constructing a linear precoding matrix of each user according to a zero-space orthogonal basis of each user interference channel matrix;
and performing linear precoding on the transmitting signals of each user by using the constructed linear precoding matrix.
Preferably, the inverse calculation is performed on the lower triangular matrix L to obtain the lower triangular matrix L
Figure BSA00000410899400042
The method comprises the following steps:
constructing a diagonal matrix G according to the lower triangular matrix L, wherein diagonal elements of the diagonal matrix G are reciprocal of the diagonal elements of the lower triangular matrix L;
constructing a unit lower triangular matrix B (GL) according to the lower triangular matrix L and the diagonal matrix G;
according to the formula
Figure BSA00000410899400043
Calculating the inverse of the unit lower triangular matrix B; wherein I is an identity matrix;
according to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L
Figure BSA00000410899400044
Preferably, the inverse of the lower triangular matrix L
Figure BSA00000410899400045
And the orthogonal matrix Q, obtaining the zero space orthogonal basis of each user interference channel matrix comprises:
calculating the said
Figure BSA00000410899400046
In each sub-matrix
Figure BSA00000410899400047
Of (2) orthogonal basis
Figure BSA00000410899400048
According to the orthogonal matrix Q and the orthogonal base
Figure BSA00000410899400049
Obtaining an interference channel matrix for an arbitrary user k
Figure BSA000004108994000410
Zero space orthogonal basis of
Figure BSA000004108994000411
Preferably, said calculating said
Figure BSA000004108994000412
In each sub-matrix
Figure BSA000004108994000413
Of (2) orthogonal basis
Figure BSA000004108994000414
The method comprises the following steps:
to the above
Figure BSA000004108994000415
Each sub-matrix inPerforming Schmidt orthogonalization to obtain the sub-matrix
Figure BSA000004108994000417
Of (2) orthogonal basis
Preferably, the constructing a linear precoding matrix for each user according to the calculated zero-space orthogonal basis of the interference channel matrix of each user includes:
constructing an equivalent channel matrix of zero co-channel interference of a user k by using a zero space orthogonal basis of an interference channel matrix of any user k and a downlink channel matrix of the user k;
and carrying out SVD on the equivalent channel matrix or QR on a conjugate transpose matrix of the equivalent channel matrix, and constructing a precoding matrix of the user k according to a decomposition result.
The BD pre-coding device provided by the invention comprises:
a total channel matrix determining module for determining a total user channel matrix according to the downlink channel matrix of each user in the system
Figure BSA00000410899400051
Wherein HkA downlink channel matrix of a user K, where K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band;
QR decomposition module for said overall user channel matrix HsConjugate transpose matrix ofQR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, and the H issConjugate transpose matrix Q represented as lower triangular matrix L and orthogonal matrix QHWhere L is the conjugate transpose of the upper triangular matrix RH；
A lower triangular matrix inversion module for performing inversion calculation on the lower triangular matrix L to obtain L - 1 = L ^ 1 L ^ 2 . . . L ^ K ;
A zero space orthogonal basis determining module for determining the orthogonal matrix Q obtained by the QR decomposition module and the lower triangular matrix obtained by the inversion module
Figure BSA00000410899400054
Obtaining a null space orthogonal basis of each user interference channel matrix;
a precoding matrix constructing module, configured to construct a linear precoding matrix for each user according to the null-space orthogonal basis of each user interference channel matrix determined by the null-space orthogonal basis determining module;
and the precoding processing module is used for performing linear precoding on the transmitting signals of each user by utilizing the linear precoding matrix constructed by the precoding matrix constructing module.
Preferably, the lower triangular matrix inversion module includes:
the first construction submodule is used for constructing a diagonal matrix G according to the lower triangular matrix L, and diagonal elements of the diagonal matrix G are inverses of the diagonal elements of the lower triangular matrix L;
a second constructing submodule, configured to construct a unit lower triangular matrix B ═ GL according to the lower triangular matrix L and the diagonal matrix G;
a first inversion submodule for expressing
Figure BSA00000410899400061
Calculating the inverse of the lower triangular matrix B; wherein I is an identity matrix;
a second inversion submodule for inverting the output signal according to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L L - 1 = L ^ 1 L ^ 2 . . . L ^ K .
Preferably, the zero space orthogonal basis determining module includes:
a first calculation submodule for calculating the inverse of the lower triangular matrix
Figure BSA00000410899400063
In each sub-matrix
Figure BSA00000410899400064
Of (2) orthogonal basis
Figure BSA00000410899400065
A second computation submodule for computing the orthogonal matrix Q and the orthogonal basis
Figure BSA00000410899400066
Obtaining an interference channel matrix for an arbitrary user k
Figure BSA00000410899400067
Zero space orthogonal basis of
Figure BSA00000410899400068
Preferably, the first computation submodule is paired with the second computation submodule
Figure BSA00000410899400069
Each sub-matrix in
Figure BSA000004108994000610
Performing Schmidt orthogonalization to obtain the sub-matrixOf (2) orthogonal basis
Figure BSA000004108994000612
Preferably, the precoding matrix constructing module includes:
the equivalent channel matrix construction submodule is used for constructing an equivalent channel matrix of zero co-channel interference of a user k by utilizing a zero space orthogonal basis of an interference channel matrix of any user k and a downlink channel matrix of the user k;
and the precoding matrix constructing submodule is used for carrying out SVD (singular value decomposition) on the equivalent channel matrix or carrying out QR (quick response) decomposition on a conjugate transpose matrix of the equivalent channel matrix and constructing the precoding matrix of the user k according to a decomposition result.
According to the scheme, QR decomposition is only carried out on the total user channel matrix once, the zero-space orthogonal basis of the interference channel matrix of each user is determined according to the QR decomposition result, and the interference channel matrix of each user does not need to be subjected to QR decomposition, so that the calculation complexity in the precoding process is reduced, and the precoding efficiency is improved.
Furthermore, the invention further reduces the calculation complexity in the precoding process and improves the precoding efficiency by carrying out simplified inversion operation on the lower triangular matrix L of QR decomposition.
Drawings
Fig. 1 is an exemplary flowchart of a BD pre-coding method according to an embodiment of the present invention.
Fig. 2 is a diagram illustrating an exemplary structure of a BD pre-encoding apparatus according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of an internal structure of a lower triangular matrix inversion module in the BD pre-encoding device according to the embodiment of the present invention.
Fig. 4 is a schematic diagram of an internal structure of a zero-space orthogonal basis determining module in the BD pre-encoding device according to the embodiment of the present invention.
Fig. 5 is a schematic diagram of an internal structure of a precoding matrix constructing module in the BD precoding device according to the embodiment of the present invention.
Fig. 6 is a simulation diagram comparing the complexity of the BD pre-coding scheme in the embodiment of the present invention with that of the BD pre-coding scheme in the prior art.
Fig. 7 is a simulation diagram comparing capacity performance of the BD pre-coding scheme in the embodiment of the present invention with that of the BD pre-coding scheme in the prior art.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the following embodiments and the accompanying drawings.
In the invention, firstly, when the zero space vectors of the matrix are orthogonal to each other, the zero space vectors can be called as the zero space orthogonal basis of the matrix, so that the interference channel matrix of any user k is obtained
Figure BSA00000410899400071
The null space orthogonal basis of (2) can firstly obtain the interference channel matrix of any user kZero space vector of
Figure BSA00000410899400073
Can be calculated by calculating the total user channel matrix
Figure BSA00000410899400074
Obtaining the pseudo-inverse of, i.e. calculating HsPseudo-inverse of
Figure BSA00000410899400075
Is provided with
Figure BSA00000410899400076
And is provided with
Figure BSA00000410899400077
Namely, it isIs thatSet of null-space vectors, by
Figure BSA000004108994000710
Performing an orthogonalization process to obtain
Figure BSA000004108994000711
A null-space orthogonal basis. Wherein N isTThe number of receiving antennas of any user K (K is 1, 2, …, K) is n, which is the number of transmitting antennas of the cell base stationkAnd K is the number of users served simultaneously by the base station using the same frequency band. The total number of receiving antennas on K user terminals is
Figure BSA00000410899400081
And, the total number of transmitting antennas N of the base stationTGreater than or equal toTotal number of receiving antennas N of user terminalR，
Figure BSA00000410899400082
Dimension N ofT×nk，
Figure BSA00000410899400083
Has a dimension of (N)R-nk)×NT。
Based on the above thought, the embodiment of the invention adopts simplified HsPseudo-inverse solution process, referring to fig. 1, fig. 1 is an exemplary flowchart of a BD pre-coding method in an embodiment of the present invention. As shown in fig. 1, the method comprises the steps of:
step 101, determining a total user channel matrix according to a downlink channel matrix of each user in a system
Figure BSA00000410899400084
Wherein HkThe downlink channel matrix of user K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band simultaneously. HsDimension of (A) is NR×NT。
In this step, the process of acquiring the downlink channel matrix of each user may be the same as that in the prior art, for example, each user may perform channel estimation according to the received pilot data to acquire the downlink channel matrix from the base station to its own user, and then the base station may acquire the downlink channel matrix of each user through channel reciprocity.
Step 102, for the total user channel matrix HsConjugate transpose matrix of
Figure BSA00000410899400085
QR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, namely
Figure BSA00000410899400086
The total user channel matrix HsExpressed as lower triangular matrix L and orthogonal matrix QConjugate transpose matrix QHProduct of, i.e.
Figure BSA00000410899400087
Wherein L is a conjugate transpose matrix R of the upper triangular matrix RH。
In this embodiment, based on the decomposition in step 102, H can be obtaineds＝LQHAt this time, the total user channel matrix H is calculated againsPseudo-inverse ofWhen it is, then there are
Figure BSA00000410899400089
Is provided with
Figure BSA000004108994000810
Namely, it is
Figure BSA000004108994000811
Is just like
Figure BSA000004108994000812
A set of null-space vectors. For this reason, the present embodiment only needs to continue solving
Figure BSA000004108994000813
Namely, the following step 103 is performed.
103, performing inversion calculation on the lower triangular matrix L to obtain
Figure BSA000004108994000814
Wherein,
Figure BSA000004108994000815
dimension of (A) is NR×nk。
In this step, the inverse operation of the matrix can be directly performed to obtain the inverse of the lower triangular matrix LAlternatively, in this step, the following simplified inversion operation procedure may be adopted to further reduce the computational complexity.
1) And constructing a diagonal matrix G according to the lower triangular matrix L, wherein the diagonal elements of the diagonal matrix G are the reciprocal of the diagonal elements of the lower triangular matrix L. Wherein, the dimension of G is NR×NR。
2) Constructing a unit lower triangular matrix according to the lower triangular matrix L and the diagonal matrix G <math> <mrow> <msub> <mi>B</mi> <mrow> <msub> <mi>N</mi> <mi>R</mi> </msub> <mo>&times;</mo> <msub> <mi>N</mi> <mi>R</mi> </msub> </mrow> </msub> <mo>=</mo> <msub> <mi>G</mi> <mrow> <msub> <mi>N</mi> <mi>R</mi> </msub> <mo>&times;</mo> <msub> <mi>N</mi> <mi>R</mi> </msub> </mrow> </msub> <msub> <mi>L</mi> <mrow> <msub> <mi>N</mi> <mi>R</mi> </msub> <mo>&times;</mo> <msub> <mi>N</mi> <mi>R</mi> </msub> </mrow> </msub> <mo>.</mo> </mrow> </math>
3) Based on the particularity of the triangular matrix under the unit, according to
Figure BSA00000410899400092
Figure BSA00000410899400093
The simplified method of (3) finds the inverse of the triangular matrix B in unity. Wherein I is an identity matrix.
4) According to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L
Figure BSA00000410899400094
104, according to the inverse of the lower triangular matrix L
Figure BSA00000410899400095
And obtaining the zero space orthogonal basis of each user interference channel matrix by the orthogonal matrix Q.
In this step, the inverse of the lower triangular matrix L can be used
Figure BSA00000410899400096
And an orthogonal matrix Q, obtaining
Figure BSA00000410899400097
Due to each sub-matrix therein
Figure BSA00000410899400098
The columns of (K-1, 2, …, K) are not orthogonal to each other, and therefore
Figure BSA00000410899400099
Is not yet
Figure BSA000004108994000910
The zero space orthogonal base of (2) is further subjected to orthogonalization, such as Schmidt orthogonalization (GSO), to obtain
Figure BSA000004108994000911
The orthogonal basis of the user k is obtained, namely the interference channel matrix of the corresponding user k
Figure BSA000004108994000912
A null-space orthogonal basis. Wherein,
Figure BSA000004108994000913
dimension of (A) is NT×nk。
Alternatively, Q is considered to be an orthogonal matrix, i.e. Q is orthogonal between the columns, so in this step, the Q is calculated
Figure BSA000004108994000914
Can only find the zero space orthogonal base
Figure BSA000004108994000915
Of (2) orthogonal basis
Figure BSA000004108994000916
Namely, it is right to
Figure BSA000004108994000917
Using GSO algorithm to obtain
Figure BSA000004108994000918
Of (2) orthogonal basis
Figure BSA000004108994000919
Accordingly, in this step, the calculation may be performed firstIn each sub-matrix
Figure BSA000004108994000921
(K is 1, 2, …, K) orthogonal base
Figure BSA000004108994000922
Then according to the orthogonal matrix Q and the orthogonal base
Figure BSA000004108994000923
Obtaining an interference channel matrix for an arbitrary user k
Figure BSA000004108994000924
Zero space orthogonal basis of
Figure BSA000004108994000925
And 105, constructing a linear precoding matrix of each user according to the zero-space orthogonal basis of the interference channel matrix of each user.
In this step, when constructing the linear precoding matrix of each user according to the null-space orthogonal basis of the interference channel matrix of each user, various implementation forms can be adopted.
For example, from the above-described zero-space orthogonal basis (e.g.
Figure BSA00000410899400101
) In selecting any nkThe column vectors are the column vectors of the linear precoding matrix for user k.
As another example, can utilize
Figure BSA00000410899400102
Zero space orthogonal basis (e.g. of
Figure BSA00000410899400103
) And the downlink channel matrix Hk of the user k constructs an equivalent channel matrix (such as the zero CCI channel matrix) of the user k
Figure BSA00000410899400104
) (ii) a Carrying out SVD on the equivalent channel matrix to obtain the front n of the right unitary matrix of the equivalent channel matrixkColumns; interference channel matrix for user k
Figure BSA00000410899400105
Zero space orthogonal basis (e.g. of
Figure BSA00000410899400106
) Front n of right unitary matrix of equivalent channel matrix corresponding to the formerkAnd performing multiplication operation on the columns, and taking the result of the multiplication as a precoding matrix of the user k.
As another example, can utilize
Figure BSA00000410899400107
Zero space orthogonal basis (e.g. of
Figure BSA00000410899400108
) And the downlink channel matrix H of user kkConstructing an equivalent channel matrix of zero CCI for user k (e.g.
Figure BSA00000410899400109
) (ii) a Performing QR decomposition on the conjugate transpose matrix of the equivalent channel matrix to obtain an orthogonal matrix Q1kAnd an upper triangular matrix R1kObtaining said orthogonal matrix Q1kFront n ofkColumns; for the orthogonal matrix Q1kFront n ofkInterference channel matrix of column and user k
Figure BSA000004108994001010
Zero space orthogonal basis (e.g. of) And performing multiplication operation, and taking the result of the multiplication as a precoding matrix of the user k.
And 106, performing linear precoding on the transmitting signals of each user by using the constructed linear precoding matrix.
The specific processing procedure of this step may be the same as that in the prior art, and is not described herein again.
The BD pre-coding method in the embodiment of the present invention is described in detail above, and the BD pre-coding apparatus in the embodiment of the present invention is described in detail below.
Referring to fig. 2, fig. 2 is a diagram illustrating an exemplary structure of a BD pre-encoding apparatus according to an embodiment of the present invention. Corresponding to the method shown in fig. 1, the apparatus in the embodiment of the present invention includes: the device comprises a total channel matrix determining module, a QR decomposition module, a lower triangular matrix inversion module, a zero-space orthogonal basis determining module, a precoding matrix constructing module and a precoding processing module.
Wherein, the total channel matrix determining module is used for determining the total user channel matrix according to the downlink channel matrix of each user in the system
Figure BSA00000410899400111
Wherein HkThe downlink channel matrix of user K is 1, 2, …, K is that the system base station is in the same stateThe number of users served simultaneously within the frequency band. HsDimension of (A) is NR×NT。
QR decomposition module for said total user channel matrix HsConjugate transpose matrix ofQR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, namely
Figure BSA00000410899400113
Subjecting said H tosConjugate transpose matrix Q represented as lower triangular matrix L and orthogonal matrix QHProduct of, i.e.
Figure BSA00000410899400114
Wherein L is a conjugate transpose matrix R of the upper triangular matrix RH。
A lower triangular matrix inversion module for performing inversion calculation on the lower triangular matrix L to obtain
Figure BSA00000410899400115
Wherein,
Figure BSA00000410899400116
dimension of (A) is NR×nk。
The zero space orthogonal basis determining module is used for obtaining the orthogonal matrix Q obtained by the QR decomposition module and the lower triangular matrix inversion module
Figure BSA00000410899400117
And obtaining the zero space orthogonal basis of the interference channel matrix of each user.
And the precoding matrix constructing module is used for constructing a linear precoding matrix of each user according to the zero-space orthogonal basis of each user interference channel matrix determined by the zero-space orthogonal basis determining module.
And the precoding processing module is used for performing linear precoding on the transmitting signals of each user by utilizing the linear precoding matrix constructed by the precoding matrix construction module.
In specific implementation, the lower triangular matrix inversion module can directly perform inversion operation on the lower triangular matrix L to obtain the inverse of the lower triangular matrix L
Figure BSA00000410899400118
Alternatively, the lower triangular matrix inversion module may also include, as shown in fig. 3: the device comprises a first construction submodule, a second construction submodule, a first inversion submodule and a second inversion submodule.
The first constructing submodule is used for constructing a diagonal matrix G according to the lower triangular matrix L, and diagonal elements of the diagonal matrix G are inverses of the diagonal elements of the lower triangular matrix L. Wherein, the dimension of G is NR×NR。
The second construction submodule is used for constructing a unit lower triangular matrix according to the lower triangular matrix L and the diagonal matrix G
Figure BSA00000410899400119
The first inversion submodule is used for following the formula
Figure BSA00000410899400122
The inverse of the lower triangular matrix B is calculated. Wherein I is an identity matrix.
The second inversion submodule is used for inverting the output signal according to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L
Figure BSA00000410899400123
Wherein,
Figure BSA00000410899400124
dimension of (A) is NR×nk。
In a specific implementation, the zero-space orthogonal basis determining module may be as shown in fig. 4, and includes: a first computation submodule and a second computation submodule.
Wherein the first computation submodule is used for inverting the lower triangular matrix L
Figure BSA00000410899400125
And an orthogonal matrix Q, obtaining
Figure BSA00000410899400126
A second computing submodule for pairing
Figure BSA00000410899400127
Each sub-matrix in
Figure BSA00000410899400128
(K-1, 2, …, K) is orthogonalized, e.g., Schmidt orthogonalized, to obtainThe orthogonal basis of the user k is obtained, namely the interference channel matrix of the corresponding user kA null-space orthogonal basis. Wherein,
Figure BSA000004108994001211
dimension of (A) is NT×nk。
Or, the first computation submodule is used for computing the result obtained by the lower triangular matrix inversion module
Figure BSA000004108994001212
In each sub-matrix
Figure BSA000004108994001213
Of (2) orthogonal basis
Figure BSA000004108994001214
A second computation submodule for computing a second vector from the orthogonal matrix Q and the orthogonal basis
Figure BSA000004108994001215
Obtaining an interference channel matrix for an arbitrary user k
Figure BSA000004108994001216
Zero space orthogonal basis of
Figure BSA000004108994001217
Wherein the first computation submodule can perform a computation on the
Figure BSA000004108994001218
Each sub-matrix in
Figure BSA000004108994001219
Performing Schmidt orthogonalization to obtain the sub-matrix
Figure BSA000004108994001220
Of (2) orthogonal basis
Figure BSA000004108994001221
In particular implementations, the precoding matrix construction module can derive the zero-space orthogonal basis (e.g., from the above-mentioned zero-space orthogonal basis)
Figure BSA000004108994001222
) In selecting any nkThe column vectors are the column vectors of the linear precoding matrix for user k. Alternatively, the precoding matrix constructing module may also include, as shown in fig. 5: an equivalent channel matrix construction submodule and a precoding matrix construction submodule.
Wherein, the equivalent channel matrix construction submodule is used for utilizing any user k to interfere the channel matrix
Figure BSA000004108994001223
Zero space orthogonal basis (e.g. of
Figure BSA000004108994001224
) And the downlink channel matrix H of user kkConstructing an equivalent channel matrix of zero CCI for user k (e.g.
Figure BSA000004108994001225
)。
A precoding matrix construction submodule for constructing the equivalent channel matrix (e.g. of the first and second sub-modules)
Figure BSA000004108994001226
) Performing SVD to obtain the front n of the right unitary matrix of the equivalent channel matrixkColumns; interference channel matrix for user k
Figure BSA00000410899400131
Zero space orthogonal basis (e.g. of
Figure BSA00000410899400132
) Front n of right unitary matrix of equivalent channel matrix corresponding to the formerkAnd performing multiplication operation on the columns, and taking the result of the multiplication as a precoding matrix of the user k.
Or, the precoding matrix constructing sub-module may also be configured to perform QR decomposition on the conjugate transpose matrix of the equivalent channel matrix to obtain an orthogonal matrix Q1kAnd an upper triangular matrix R1kObtaining said orthogonal matrix Q1kFront n ofkColumns; for the orthogonal matrix Q1kFront n ofkInterference channel matrix of column and user k
Figure BSA00000410899400133
Zero space orthogonal basis (e.g. of
Figure BSA00000410899400134
) And performing multiplication operation, and taking the result of the multiplication as a precoding matrix of the user k.
The BD pre-coding method and apparatus in the embodiments of the present invention are described in detail above. The technical scheme in the embodiment of the invention can be used for the condition that the number of the receiving antennas of the user is the same as the number of the data streams communicated by the user, and can also be used for the condition that the number of the receiving antennas of the user is different from the number of the data streams communicated by the user. For different situations, the receiving end only needs to perform the combining processing of the receiving antennas. Common techniques for processing the receiving antenna include antenna selection, mrc (maximum ratio combining), and QBC (equalization-based combining).
In the embodiment of the invention, QR decomposition is carried out only once on the total user channel matrix, and QR decomposition is not required to be carried out on the interference channel matrix of each user, so that the calculation complexity in the precoding process is reduced, and the precoding efficiency is improved.
Furthermore, the invention further reduces the calculation complexity in the precoding process and improves the precoding efficiency by carrying out simplified inversion operation on the lower triangular matrix L of QR decomposition.
The following is a simulation comparison of the complexity and capacity performance of the BD precoding scheme in the embodiment of the present invention and the BD precoding scheme in the prior art.
Fig. 6 is a simulation diagram comparing the complexity of the BD pre-coding scheme in the embodiment of the present invention with that of the BD pre-coding scheme in the prior art. As shown in fig. 6, the conventional BD precoding scheme has the highest complexity, and the QR decomposition-based BD precoding scheme has the second highest complexity. Compared with the BD pre-coding scheme in the embodiment of the present invention, the BD pre-coding scheme in the embodiment of the present invention has a performance advantage of significantly reducing complexity. It can be seen that the BD precoding scheme in the embodiments of the present invention has a significant advantage in reducing complexity performance even when the number of users served by the base station is continuously increased.
Fig. 7 is a simulation diagram comparing the capacity performance of the BD pre-coding scheme in the embodiment of the present invention with that of the BD pre-coding scheme in the prior art under different snr conditions. Wherein, the simulation conditions are as follows: the number of base station antennas is 6, the number of antennas of each user is 2, the number of users is 3, and a channel model is modeled into a perfect single-path Rayleigh channel. The signal transmission power of the BS end is 1. As shown in fig. 7, the BD pre-coding scheme in the embodiment of the present invention has the same system capacity performance as the existing BD pre-coding scheme. Therefore, the technical scheme of the embodiment of the invention is used for linear precoding processing, thereby reducing the complexity of the system algorithm and simultaneously not causing performance loss to the system.
Therefore, the technical scheme in the embodiment of the invention can effectively reduce the complexity of the algorithm under the condition of ensuring that the system performance is not lost, which can undoubtedly reduce the complexity of the base station side, particularly the hardware configuration of the user side, and also conforms to the principle of communication system design.
Those skilled in the art will appreciate that the modules in the devices in the embodiments may be distributed in the devices in the embodiments according to the description of the embodiments, and may be correspondingly changed in one or more devices different from the embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
Some steps in the embodiments of the present invention may be implemented by software, and the corresponding software program may be stored in a readable storage medium, such as an optical disc or a hard disk.
The above-mentioned embodiments are intended to illustrate the objects, aspects and advantages of the present invention, and it should be understood that the above-mentioned embodiments are merely preferred embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A block diagonalizing precoding method, the method comprising:
determining a total user channel matrix according to a downlink channel matrix of each user in the system
Figure FSA00000410899300011
Wherein HkA downlink channel matrix of a user K, where K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band;
for the total user channel momentMatrix HsConjugate transpose matrix of
Figure FSA00000410899300012
QR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, and the total user channel matrix H is obtainedsConjugate transpose matrix Q represented as lower triangular matrix L and orthogonal matrix QHWhere L is the conjugate transpose of the upper triangular matrix RH；
Performing inversion calculation on the lower triangular matrix L to obtain
Figure FSA00000410899300013
According to the inverse of the lower triangular matrix L
Figure FSA00000410899300014
Obtaining a zero space orthogonal base of each user interference channel matrix;
constructing a linear precoding matrix of each user according to a zero-space orthogonal basis of each user interference channel matrix;
and performing linear precoding on the transmitting signals of each user by using the constructed linear precoding matrix.
2. The method of claim 1, wherein the inverse computation of the lower triangular matrix L results in
Figure FSA00000410899300015
The method comprises the following steps:
constructing a diagonal matrix G according to the lower triangular matrix L, wherein diagonal elements of the diagonal matrix G are reciprocal of the diagonal elements of the lower triangular matrix L;
constructing a unit lower triangular matrix B (GL) according to the lower triangular matrix L and the diagonal matrix G;
according to the formulaCalculating the inverse of the unit lower triangular matrix B; wherein I is an identity matrix;
according to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L
Figure FSA00000410899300017
3. The method of claim 1, wherein the inverse of L is based on a lower triangular matrixAnd the orthogonal matrix Q, obtaining the zero space orthogonal basis of each user interference channel matrix comprises:
calculating the said
Figure FSA00000410899300022
In each sub-matrix
Figure FSA00000410899300023
Of (2) orthogonal basis
Figure FSA00000410899300024
According to the orthogonal matrix Q and the orthogonal base
Figure FSA00000410899300025
Obtaining an interference channel matrix for an arbitrary user kZero space orthogonal basis of
4. The method of claim 3, wherein said calculating said
Figure FSA00000410899300028
In each sub-matrix
Figure FSA00000410899300029
Of (2) orthogonal basis
Figure FSA000004108993000210
The method comprises the following steps:
to the above
Figure FSA000004108993000211
Each sub-matrix in
Figure FSA000004108993000212
Performing Schmidt orthogonalization to obtain the sub-matrix
Figure FSA000004108993000213
Of (2) orthogonal basis
Figure FSA000004108993000214
5. The method according to any of claims 1 to 4, wherein said constructing a linear precoding matrix for each user based on the computed zero-space orthogonal basis of the interfering channel matrices of the respective users comprises:
constructing an equivalent channel matrix of zero co-channel interference of a user k by using a zero space orthogonal basis of an interference channel matrix of any user k and a downlink channel matrix of the user k;
and carrying out SVD on the equivalent channel matrix or QR on a conjugate transpose matrix of the equivalent channel matrix, and constructing a precoding matrix of the user k according to a decomposition result.
6. A block diagonalizing precoding apparatus, comprising:
total channel matrix determination module for rootDetermining a total user channel matrix according to a downlink channel matrix of each user in a system
Figure FSA000004108993000215
Wherein HkA downlink channel matrix of a user K, where K is 1, 2, …, and K is the number of users served by the system base station in the same frequency band;
QR decomposition module for said overall user channel matrix HsConjugate transpose matrix of
Figure FSA000004108993000216
QR decomposition is carried out to obtain the product of an orthogonal matrix Q and an upper triangular matrix R, and the H issConjugate transpose matrix Q represented as lower triangular matrix L and orthogonal matrix QHWhere L is the conjugate transpose of the upper triangular matrix RH；
A lower triangular matrix inversion module for performing inversion calculation on the lower triangular matrix L to obtain L - 1 = L ^ 1 L ^ 2 . . . L ^ K ;
Zero space orthogonalityA base determination module for obtaining the orthogonal matrix Q obtained by the QR decomposition module and the lower triangular matrix inversion module
Figure FSA00000410899300031
Obtaining a null space orthogonal basis of each user interference channel matrix;
a precoding matrix constructing module, configured to construct a linear precoding matrix for each user according to the null-space orthogonal basis of each user interference channel matrix determined by the null-space orthogonal basis determining module;
and the precoding processing module is used for performing linear precoding on the transmitting signals of each user by utilizing the linear precoding matrix constructed by the precoding matrix constructing module.
7. The apparatus of claim 6, wherein the lower triangular matrix inversion module comprises:
the first construction submodule is used for constructing a diagonal matrix G according to the lower triangular matrix L, and diagonal elements of the diagonal matrix G are inverses of the diagonal elements of the lower triangular matrix L;
a second constructing submodule, configured to construct a unit lower triangular matrix B ═ GL according to the lower triangular matrix L and the diagonal matrix G;
a first inversion submodule for expressing
Figure FSA00000410899300032
Calculating the inverse of the lower triangular matrix B; wherein I is an identity matrix;
a second inversion submodule for inverting the output signal according to L-1＝B-1G, obtaining the inverse of the lower triangular matrix L L - 1 = L ^ 1 L ^ 2 . . . L ^ K .
8. The apparatus of claim 6, wherein the zero-space orthogonal basis determining module comprises:
a first calculation submodule for calculating the inverse of the lower triangular matrix
Figure FSA00000410899300034
In each sub-matrix
Figure FSA00000410899300035
Of (2) orthogonal basis
Figure FSA00000410899300036
A second computation submodule for computing the orthogonal matrix Q and the orthogonal basis
Figure FSA00000410899300037
Obtaining an interference channel matrix for an arbitrary user k
Figure FSA00000410899300038
Zero space orthogonal basis of
Figure FSA00000410899300039
9. The apparatus of claim 8, wherein the first computation submodule pairs theEach sub-matrix inPerforming Schmidt orthogonalization to obtain the sub-matrix
Figure FSA000004108993000312
Of (2) orthogonal basis
10. The apparatus of any of claims 6-9, wherein the precoding matrix construction module comprises:
the equivalent channel matrix construction submodule is used for constructing an equivalent channel matrix of zero co-channel interference of a user k by utilizing a zero space orthogonal basis of an interference channel matrix of any user k and a downlink channel matrix of the user k;
and the precoding matrix constructing submodule is used for carrying out SVD (singular value decomposition) on the equivalent channel matrix or carrying out QR (quick response) decomposition on a conjugate transpose matrix of the equivalent channel matrix and constructing the precoding matrix of the user k according to a decomposition result.
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